Overview

Brought to you by YData

Dataset statistics

Number of variables10
Number of observations204
Missing cells64
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.1 KiB
Average record size in memory80.6 B

Variable types

Text1
Numeric9

Alerts

SuicideRate_BothSexes_RatePer100k_2019 is highly overall correlated with SuicideRate_BothSexes_RatePer100k_2020 and 7 other fieldsHigh correlation
SuicideRate_BothSexes_RatePer100k_2020 is highly overall correlated with SuicideRate_BothSexes_RatePer100k_2019 and 7 other fieldsHigh correlation
SuicideRate_BothSexes_RatePer100k_2021 is highly overall correlated with SuicideRate_BothSexes_RatePer100k_2019 and 7 other fieldsHigh correlation
SuicideRate_Female_RatePer100k_2019 is highly overall correlated with SuicideRate_BothSexes_RatePer100k_2019 and 7 other fieldsHigh correlation
SuicideRate_Female_RatePer100k_2020 is highly overall correlated with SuicideRate_BothSexes_RatePer100k_2019 and 7 other fieldsHigh correlation
SuicideRate_Female_RatePer100k_2021 is highly overall correlated with SuicideRate_BothSexes_RatePer100k_2019 and 7 other fieldsHigh correlation
SuicideRate_Male_RatePer100k_2019 is highly overall correlated with SuicideRate_BothSexes_RatePer100k_2019 and 7 other fieldsHigh correlation
SuicideRate_Male_RatePer100k_2020 is highly overall correlated with SuicideRate_BothSexes_RatePer100k_2019 and 7 other fieldsHigh correlation
SuicideRate_Male_RatePer100k_2021 is highly overall correlated with SuicideRate_BothSexes_RatePer100k_2019 and 7 other fieldsHigh correlation
SuicideRate_BothSexes_RatePer100k_2019 has 21 (10.3%) missing values Missing
SuicideRate_Male_RatePer100k_2019 has 22 (10.8%) missing values Missing
SuicideRate_Female_RatePer100k_2019 has 21 (10.3%) missing values Missing
country has unique values Unique

Reproduction

Analysis started2024-10-31 02:48:56.302673
Analysis finished2024-10-31 02:49:07.492057
Duration11.19 seconds
Software versionydata-profiling vv4.11.0
Download configurationconfig.json

Variables

country
Text

Unique 

Distinct204
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-10-31T08:19:07.997260image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length32
Median length22
Mean length8.5980392
Min length4

Characters and Unicode

Total characters1754
Distinct characters52
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique204 ?
Unique (%)100.0%

Sample

1st rowIndia
2nd rowChina
3rd rowUnited States
4th rowIndonesia
5th rowPakistan
ValueCountFrequency (%)
and 6
 
2.3%
islands 5
 
1.9%
republic 4
 
1.5%
united 4
 
1.5%
guinea 3
 
1.1%
saint 3
 
1.1%
south 3
 
1.1%
states 2
 
0.8%
north 2
 
0.8%
samoa 2
 
0.8%
Other values (222) 227
87.0%
2024-10-31T08:19:08.664340image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 269
15.3%
i 151
 
8.6%
n 141
 
8.0%
e 119
 
6.8%
r 99
 
5.6%
o 95
 
5.4%
u 70
 
4.0%
t 68
 
3.9%
l 62
 
3.5%
s 59
 
3.4%
Other values (42) 621
35.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1440
82.1%
Uppercase Letter 255
 
14.5%
Space Separator 57
 
3.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 269
18.7%
i 151
10.5%
n 141
9.8%
e 119
 
8.3%
r 99
 
6.9%
o 95
 
6.6%
u 70
 
4.9%
t 68
 
4.7%
l 62
 
4.3%
s 59
 
4.1%
Other values (16) 307
21.3%
Uppercase Letter
ValueCountFrequency (%)
S 31
12.2%
M 21
 
8.2%
B 20
 
7.8%
C 19
 
7.5%
G 16
 
6.3%
A 16
 
6.3%
N 15
 
5.9%
T 15
 
5.9%
I 14
 
5.5%
P 12
 
4.7%
Other values (14) 76
29.8%
Space Separator
ValueCountFrequency (%)
57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1695
96.6%
Common 59
 
3.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 269
15.9%
i 151
 
8.9%
n 141
 
8.3%
e 119
 
7.0%
r 99
 
5.8%
o 95
 
5.6%
u 70
 
4.1%
t 68
 
4.0%
l 62
 
3.7%
s 59
 
3.5%
Other values (40) 562
33.2%
Common
ValueCountFrequency (%)
57
96.6%
- 2
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1754
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 269
15.3%
i 151
 
8.6%
n 141
 
8.0%
e 119
 
6.8%
r 99
 
5.6%
o 95
 
5.4%
u 70
 
4.0%
t 68
 
3.9%
l 62
 
3.5%
s 59
 
3.4%
Other values (42) 621
35.4%

SuicideRate_BothSexes_RatePer100k_2021
Real number (ℝ)

High correlation 

Distinct195
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.5259314
Minimum0.78
Maximum59.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-10-31T08:19:08.862563image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.78
5-th percentile2.0075
Q15.09
median7.885
Q312.9125
95-th percentile20.3995
Maximum59.62
Range58.84
Interquartile range (IQR)7.8225

Descriptive statistics

Standard deviation6.802563
Coefficient of variation (CV)0.71411002
Kurtosis13.844656
Mean9.5259314
Median Absolute Deviation (MAD)3.71
Skewness2.5191409
Sum1943.29
Variance46.274864
MonotonicityNot monotonic
2024-10-31T08:19:09.021876image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.09 2
 
1.0%
15.59 2
 
1.0%
5.43 2
 
1.0%
4.28 2
 
1.0%
15.83 2
 
1.0%
5.53 2
 
1.0%
3.55 2
 
1.0%
9.72 2
 
1.0%
9.17 2
 
1.0%
8.49 1
 
0.5%
Other values (185) 185
90.7%
ValueCountFrequency (%)
0.78 1
0.5%
0.89 1
0.5%
0.94 1
0.5%
1.01 1
0.5%
1.04 1
0.5%
1.07 1
0.5%
1.15 1
0.5%
1.38 1
0.5%
1.43 1
0.5%
1.64 1
0.5%
ValueCountFrequency (%)
59.62 1
0.5%
31.26 1
0.5%
27.91 1
0.5%
25.81 1
0.5%
24.1 1
0.5%
23.6 1
0.5%
23.55 1
0.5%
23.17 1
0.5%
21.31 1
0.5%
20.57 1
0.5%

SuicideRate_Male_RatePer100k_2021
Real number (ℝ)

High correlation 

Distinct198
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.802304
Minimum1.18
Maximum86.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-10-31T08:19:09.264542image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1.18
5-th percentile2.7975
Q17.5775
median12.205
Q319.8575
95-th percentile34.352
Maximum86.96
Range85.78
Interquartile range (IQR)12.28

Descriptive statistics

Standard deviation10.840661
Coefficient of variation (CV)0.73236311
Kurtosis9.6158727
Mean14.802304
Median Absolute Deviation (MAD)5.73
Skewness2.1992999
Sum3019.67
Variance117.51994
MonotonicityNot monotonic
2024-10-31T08:19:09.445975image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.57 2
 
1.0%
25.66 2
 
1.0%
12.25 2
 
1.0%
12.19 2
 
1.0%
6.02 2
 
1.0%
6.46 2
 
1.0%
20.03 1
 
0.5%
14.19 1
 
0.5%
25.68 1
 
0.5%
36.61 1
 
0.5%
Other values (188) 188
92.2%
ValueCountFrequency (%)
1.18 1
0.5%
1.24 1
0.5%
1.44 1
0.5%
1.48 1
0.5%
1.49 1
0.5%
1.6 1
0.5%
1.77 1
0.5%
2.21 1
0.5%
2.44 1
0.5%
2.5 1
0.5%
ValueCountFrequency (%)
86.96 1
0.5%
52.79 1
0.5%
49.96 1
0.5%
41.82 1
0.5%
41.4 1
0.5%
37.42 1
0.5%
36.96 1
0.5%
36.61 1
0.5%
35.68 1
0.5%
35.11 1
0.5%

SuicideRate_Female_RatePer100k_2021
Real number (ℝ)

High correlation 

Distinct181
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3582843
Minimum0.3
Maximum29.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-10-31T08:19:09.602070image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.6975
Q12.2625
median3.54
Q35.785
95-th percentile10.1285
Maximum29.4
Range29.1
Interquartile range (IQR)3.5225

Descriptive statistics

Standard deviation3.3110813
Coefficient of variation (CV)0.75972128
Kurtosis15.417258
Mean4.3582843
Median Absolute Deviation (MAD)1.58
Skewness2.6963599
Sum889.09
Variance10.96326
MonotonicityNot monotonic
2024-10-31T08:19:09.764701image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.79 4
 
2.0%
2.91 2
 
1.0%
3.12 2
 
1.0%
3.54 2
 
1.0%
1.67 2
 
1.0%
2.59 2
 
1.0%
3.93 2
 
1.0%
4.44 2
 
1.0%
5.77 2
 
1.0%
3.84 2
 
1.0%
Other values (171) 182
89.2%
ValueCountFrequency (%)
0.3 1
0.5%
0.31 1
0.5%
0.33 1
0.5%
0.39 1
0.5%
0.44 2
1.0%
0.46 1
0.5%
0.5 1
0.5%
0.52 1
0.5%
0.62 1
0.5%
0.69 1
0.5%
ValueCountFrequency (%)
29.4 1
0.5%
14.58 1
0.5%
12.39 1
0.5%
11.97 1
0.5%
11.79 1
0.5%
10.85 1
0.5%
10.65 1
0.5%
10.51 1
0.5%
10.31 1
0.5%
10.29 1
0.5%

SuicideRate_BothSexes_RatePer100k_2020
Real number (ℝ)

High correlation 

Distinct198
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.669951
Minimum0.77
Maximum837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-10-31T08:19:09.951527image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.77
5-th percentile2.103
Q15.075
median8.015
Q313.0375
95-th percentile20.157
Maximum837
Range836.23
Interquartile range (IQR)7.9625

Descriptive statistics

Standard deviation58.351062
Coefficient of variation (CV)4.2685641
Kurtosis198.07213
Mean13.669951
Median Absolute Deviation (MAD)3.71
Skewness13.976837
Sum2788.67
Variance3404.8464
MonotonicityNot monotonic
2024-10-31T08:19:10.129372image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.56 2
 
1.0%
6.12 2
 
1.0%
11.27 2
 
1.0%
3.59 2
 
1.0%
11.66 2
 
1.0%
8.14 2
 
1.0%
5.6 1
 
0.5%
8.8 1
 
0.5%
9.58 1
 
0.5%
15.94 1
 
0.5%
Other values (188) 188
92.2%
ValueCountFrequency (%)
0.77 1
0.5%
0.89 1
0.5%
0.93 1
0.5%
1.02 1
0.5%
1.05 1
0.5%
1.06 1
0.5%
1.13 1
0.5%
1.37 1
0.5%
1.49 1
0.5%
1.66 1
0.5%
ValueCountFrequency (%)
837 1
0.5%
64.6 1
0.5%
31.71 1
0.5%
28.07 1
0.5%
25.63 1
0.5%
25.17 1
0.5%
24.25 1
0.5%
23.66 1
0.5%
22.9 1
0.5%
20.77 1
0.5%

SuicideRate_Male_RatePer100k_2020
Real number (ℝ)

High correlation 

Distinct197
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.922108
Minimum1.18
Maximum94.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-10-31T08:19:10.288520image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1.18
5-th percentile2.9305
Q17.5
median12.41
Q319.8975
95-th percentile33.276
Maximum94.39
Range93.21
Interquartile range (IQR)12.3975

Descriptive statistics

Standard deviation11.127588
Coefficient of variation (CV)0.74571153
Kurtosis12.648168
Mean14.922108
Median Absolute Deviation (MAD)5.89
Skewness2.4895881
Sum3044.11
Variance123.82321
MonotonicityNot monotonic
2024-10-31T08:19:10.450312image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.7 2
 
1.0%
12.42 2
 
1.0%
19.98 2
 
1.0%
8.69 2
 
1.0%
18.3 2
 
1.0%
8.43 2
 
1.0%
12.87 2
 
1.0%
15.77 1
 
0.5%
5.12 1
 
0.5%
14.83 1
 
0.5%
Other values (187) 187
91.7%
ValueCountFrequency (%)
1.18 1
0.5%
1.2 1
0.5%
1.43 1
0.5%
1.49 1
0.5%
1.5 1
0.5%
1.59 1
0.5%
1.73 1
0.5%
2.23 1
0.5%
2.32 1
0.5%
2.74 1
0.5%
ValueCountFrequency (%)
94.39 1
0.5%
53.32 1
0.5%
50.46 1
0.5%
42.42 1
0.5%
40.96 1
0.5%
40.11 1
0.5%
36.61 1
0.5%
35.25 1
0.5%
35.07 1
0.5%
34.15 1
0.5%

SuicideRate_Female_RatePer100k_2020
Real number (ℝ)

High correlation 

Distinct186
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4005392
Minimum0.29
Maximum31.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-10-31T08:19:10.607076image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.29
5-th percentile0.6945
Q12.2825
median3.52
Q35.9
95-th percentile10.2455
Maximum31.59
Range31.3
Interquartile range (IQR)3.6175

Descriptive statistics

Standard deviation3.4021861
Coefficient of variation (CV)0.77312936
Kurtosis19.322981
Mean4.4005392
Median Absolute Deviation (MAD)1.59
Skewness3.0326283
Sum897.71
Variance11.57487
MonotonicityNot monotonic
2024-10-31T08:19:10.797386image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 3
 
1.5%
1.48 3
 
1.5%
3.6 2
 
1.0%
0.43 2
 
1.0%
2.85 2
 
1.0%
2.7 2
 
1.0%
1.83 2
 
1.0%
2.6 2
 
1.0%
6.17 2
 
1.0%
5.9 2
 
1.0%
Other values (176) 182
89.2%
ValueCountFrequency (%)
0.29 1
0.5%
0.32 1
0.5%
0.34 1
0.5%
0.39 1
0.5%
0.43 2
1.0%
0.46 1
0.5%
0.51 1
0.5%
0.52 1
0.5%
0.61 1
0.5%
0.69 1
0.5%
ValueCountFrequency (%)
31.59 1
0.5%
14.56 1
0.5%
12.38 1
0.5%
12.05 1
0.5%
11.86 1
0.5%
10.73 1
0.5%
10.71 1
0.5%
10.59 1
0.5%
10.58 1
0.5%
10.54 1
0.5%

SuicideRate_BothSexes_RatePer100k_2019
Real number (ℝ)

High correlation  Missing 

Distinct115
Distinct (%)62.8%
Missing21
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean9.4551913
Minimum0.4
Maximum72.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-10-31T08:19:10.965052image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.4
5-th percentile2.22
Q14.6
median7.5
Q311.85
95-th percentile23.31
Maximum72.4
Range72
Interquartile range (IQR)7.25

Descriptive statistics

Standard deviation7.9896198
Coefficient of variation (CV)0.84499823
Kurtosis21.516496
Mean9.4551913
Median Absolute Deviation (MAD)3.4
Skewness3.5016438
Sum1730.3
Variance63.834025
MonotonicityNot monotonic
2024-10-31T08:19:11.134175image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.1 4
 
2.0%
5.4 4
 
2.0%
7.9 4
 
2.0%
9 4
 
2.0%
9.7 3
 
1.5%
6.7 3
 
1.5%
14.7 3
 
1.5%
8.1 3
 
1.5%
11.8 3
 
1.5%
2.9 3
 
1.5%
Other values (105) 149
73.0%
(Missing) 21
 
10.3%
ValueCountFrequency (%)
0.4 1
 
0.5%
0.6 1
 
0.5%
0.7 1
 
0.5%
1 1
 
0.5%
1.5 1
 
0.5%
1.6 1
 
0.5%
2 1
 
0.5%
2.1 2
1.0%
2.2 1
 
0.5%
2.4 3
1.5%
ValueCountFrequency (%)
72.4 1
0.5%
40.3 1
0.5%
29.4 1
0.5%
28.6 1
0.5%
28.3 1
0.5%
28.2 1
0.5%
26.1 1
0.5%
25.4 1
0.5%
25.1 1
0.5%
23.5 1
0.5%

SuicideRate_Male_RatePer100k_2019
Real number (ℝ)

High correlation  Missing 

Distinct135
Distinct (%)74.2%
Missing22
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean14.732418
Minimum0.6
Maximum116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-10-31T08:19:11.312638image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile3.505
Q16.825
median11.35
Q317.975
95-th percentile38.74
Maximum116
Range115.4
Interquartile range (IQR)11.15

Descriptive statistics

Standard deviation13.108952
Coefficient of variation (CV)0.88980321
Kurtosis20.126547
Mean14.732418
Median Absolute Deviation (MAD)5.25
Skewness3.441216
Sum2681.3
Variance171.84463
MonotonicityNot monotonic
2024-10-31T08:19:11.480909image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.8 4
 
2.0%
9.2 4
 
2.0%
7 3
 
1.5%
14.9 3
 
1.5%
5.7 3
 
1.5%
6.6 3
 
1.5%
8.4 3
 
1.5%
7.6 3
 
1.5%
5.9 2
 
1.0%
17.6 2
 
1.0%
Other values (125) 152
74.5%
(Missing) 22
 
10.8%
ValueCountFrequency (%)
0.6 1
0.5%
0.9 1
0.5%
1.3 1
0.5%
2.2 1
0.5%
2.5 1
0.5%
3.1 2
1.0%
3.2 1
0.5%
3.3 1
0.5%
3.5 1
0.5%
3.6 1
0.5%
ValueCountFrequency (%)
116 1
0.5%
63 1
0.5%
55.1 1
0.5%
48.6 1
0.5%
45.4 1
0.5%
43.6 1
0.5%
43.2 1
0.5%
40.2 1
0.5%
39.2 1
0.5%
38.8 1
0.5%

SuicideRate_Female_RatePer100k_2019
Real number (ℝ)

High correlation  Missing 

Distinct78
Distinct (%)42.6%
Missing21
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean4.3508197
Minimum0.3
Maximum30.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-10-31T08:19:11.837442image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.8
Q12
median3.3
Q36.05
95-th percentile9.59
Maximum30.1
Range29.8
Interquartile range (IQR)4.05

Descriptive statistics

Standard deviation3.531769
Coefficient of variation (CV)0.81174796
Kurtosis15.926585
Mean4.3508197
Median Absolute Deviation (MAD)1.5
Skewness2.9498907
Sum796.2
Variance12.473392
MonotonicityNot monotonic
2024-10-31T08:19:12.004391image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 7
 
3.4%
1.7 7
 
3.4%
2.8 7
 
3.4%
3 6
 
2.9%
3.2 6
 
2.9%
0.7 5
 
2.5%
2.7 5
 
2.5%
3.3 5
 
2.5%
1.9 5
 
2.5%
7.6 5
 
2.5%
Other values (68) 125
61.3%
(Missing) 21
 
10.3%
ValueCountFrequency (%)
0.3 1
 
0.5%
0.6 1
 
0.5%
0.7 5
2.5%
0.8 5
2.5%
1 2
 
1.0%
1.1 3
1.5%
1.2 3
1.5%
1.3 3
1.5%
1.4 2
 
1.0%
1.6 2
 
1.0%
ValueCountFrequency (%)
30.1 1
0.5%
17.4 1
0.5%
16.9 1
0.5%
12.7 1
0.5%
11.8 2
1.0%
11.1 1
0.5%
10.4 1
0.5%
9.8 1
0.5%
9.6 1
0.5%
9.5 1
0.5%

Interactions

2024-10-31T08:19:05.774949image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:57.029418image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:58.158322image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:59.282088image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:00.347953image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:01.394950image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:02.408496image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:03.448121image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:04.578227image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:05.880556image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:57.187535image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:58.267436image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:59.391276image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:00.466378image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:01.511609image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:02.529617image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:03.576217image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:04.696292image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:05.996002image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:57.312121image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:58.378134image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:59.497357image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:00.568555image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:01.613760image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:02.650137image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:03.696199image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:04.981744image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:06.116522image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:57.462549image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:58.483049image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:59.614568image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:00.691783image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:01.725440image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:02.760077image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:03.812406image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:05.098253image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:06.217500image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:57.564429image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:58.596780image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:59.729732image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:00.822345image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:01.865882image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:02.864616image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:03.929783image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:05.212566image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:06.332427image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:57.665653image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:58.697447image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:59.864219image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:00.930919image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:01.953226image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:02.965213image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:04.080114image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:05.322256image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:06.481235image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:57.810466image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:58.814201image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:59.977244image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:01.049043image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:02.062898image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:03.082162image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:04.214643image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:05.433003image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:06.650711image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:57.931382image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:58.964597image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:00.123653image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:01.168025image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:02.179245image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:03.216287image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:04.332646image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:05.550257image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:06.766371image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:58.045830image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:18:59.144793image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:00.242195image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:01.282525image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:02.293049image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:03.331130image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:04.448236image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-31T08:19:05.656204image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-10-31T08:19:12.117403image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
SuicideRate_BothSexes_RatePer100k_2019SuicideRate_BothSexes_RatePer100k_2020SuicideRate_BothSexes_RatePer100k_2021SuicideRate_Female_RatePer100k_2019SuicideRate_Female_RatePer100k_2020SuicideRate_Female_RatePer100k_2021SuicideRate_Male_RatePer100k_2019SuicideRate_Male_RatePer100k_2020SuicideRate_Male_RatePer100k_2021
SuicideRate_BothSexes_RatePer100k_20191.0000.8930.9040.8790.8480.8470.9880.8830.880
SuicideRate_BothSexes_RatePer100k_20200.8931.0000.9920.7580.9000.8970.9020.9820.981
SuicideRate_BothSexes_RatePer100k_20210.9040.9921.0000.7730.9110.9100.9100.9840.987
SuicideRate_Female_RatePer100k_20190.8790.7580.7731.0000.8740.8730.8100.7080.707
SuicideRate_Female_RatePer100k_20200.8480.9000.9110.8741.0000.9990.8090.8420.843
SuicideRate_Female_RatePer100k_20210.8470.8970.9100.8730.9991.0000.8070.8390.842
SuicideRate_Male_RatePer100k_20190.9880.9020.9100.8100.8090.8071.0000.9060.903
SuicideRate_Male_RatePer100k_20200.8830.9820.9840.7080.8420.8390.9061.0000.997
SuicideRate_Male_RatePer100k_20210.8800.9810.9870.7070.8430.8420.9030.9971.000

Missing values

2024-10-31T08:19:06.919433image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-10-31T08:19:07.149740image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-10-31T08:19:07.386145image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

countrySuicideRate_BothSexes_RatePer100k_2021SuicideRate_Male_RatePer100k_2021SuicideRate_Female_RatePer100k_2021SuicideRate_BothSexes_RatePer100k_2020SuicideRate_Male_RatePer100k_2020SuicideRate_Female_RatePer100k_2020SuicideRate_BothSexes_RatePer100k_2019SuicideRate_Male_RatePer100k_2019SuicideRate_Female_RatePer100k_2019
0India13.3315.7010.8513.2815.7010.7312.714.111.1
1China9.1710.647.639.0410.527.508.19.86.2
2United States15.2524.136.6615.3824.336.7316.125.07.5
3Indonesia1.642.211.051.662.231.072.43.71.1
4Pakistan5.828.463.055.898.543.108.913.34.3
5Nigeria4.277.221.564.307.281.553.55.01.9
6Brazil7.7812.473.307.7512.463.256.910.93.0
7Bangladesh3.675.182.213.705.182.263.75.71.7
8Russia24.1041.828.6624.2542.428.4425.143.69.1
9Ethiopia6.179.402.886.129.342.845.47.73.1
countrySuicideRate_BothSexes_RatePer100k_2021SuicideRate_Male_RatePer100k_2021SuicideRate_Female_RatePer100k_2021SuicideRate_BothSexes_RatePer100k_2020SuicideRate_Male_RatePer100k_2020SuicideRate_Female_RatePer100k_2020SuicideRate_BothSexes_RatePer100k_2019SuicideRate_Male_RatePer100k_2019SuicideRate_Female_RatePer100k_2019
194Northern Mariana Islands15.5924.665.5513.2119.875.84NaNNaNNaN
195Monaco15.4221.339.8415.5021.429.90NaNNaNNaN
196Marshall Islands20.0429.0110.6520.1129.0710.71NaNNaNNaN
197San Marino7.5912.193.288.0112.873.45NaNNaNNaN
198Palau14.9917.1212.3915.0417.2212.38NaNNaNNaN
199Cook Islands9.1714.393.9511.6318.305.32NaNNaNNaN
200Nauru23.5535.1111.7923.6635.2511.86NaNNaNNaN
201Tuvalu16.4923.798.5616.6123.928.68NaNNaNNaN
202Tokelau15.8319.5411.9715.9519.7112.05NaNNaNNaN
203Niue15.5920.6210.5115.6320.6610.54NaNNaNNaN